Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. An apparatus configured to adjust board support package (BSP)-chipset level parameters in response to changes in the apparatus or an environment in which the apparatus is located, the apparatus comprising: a microphone configured to receive one or more audio recording samples of the environment in which the apparatus is located; and a processor in communication with the microphone, wherein the processor is configured to: receive the one or more audio recording samples from the microphone; analyze the one or more audio recording samples to determine a background noise intensity; determine a customization profile by associating the background noise intensity with a pre-loaded condition selected from a set of pre-loaded conditions stored in a database, wherein the pre-loaded condition comprises one or more values that define the customization profile including a predefined chipset configuration profile having a chipset specification defined in a XML file; and cause one or more BSP-chipset level parameters to be adjusted in real time by applying the chipset specification of the customization profile, wherein the one or more BSP-chipset level parameters include one or more operational parameters associated with at least one hardware unit or a chipset in a user device and accessible through a BSP, wherein causing the one or more BSP-chipset level parameters to be adjusted in real time by applying the chipset specification of the customization profile comprises adjusting operational parameters within a broader range than accessible on a user interface or adjusting operational parameters not accessible on the user interface.
This invention relates to an apparatus that dynamically adjusts board support package (BSP)-chipset level parameters in response to environmental changes. The apparatus includes a microphone to capture audio samples from the surrounding environment and a processor that analyzes these samples to determine background noise intensity. Based on this analysis, the processor selects a pre-loaded condition from a stored database, which defines a customization profile. This profile includes a predefined chipset configuration specified in an XML file. The processor then applies this configuration to adjust BSP-chipset level parameters in real time. These parameters control hardware unit or chipset operations in a user device, accessible through the BSP. The adjustments can modify operational parameters beyond the range or accessibility of standard user interfaces, enabling finer or otherwise inaccessible tuning. The system ensures optimal device performance by adapting to environmental conditions, such as varying noise levels, without manual intervention. The solution addresses the challenge of static hardware configurations that fail to adapt to dynamic environments, improving user experience and device efficiency.
2. The apparatus of claim 1 , wherein the processor is further configured to cause the one or more BSP-chipset level parameters to be adjusted in real time based on the pre-loaded condition by communicating with the chipset to modify the one or more BSP-chipset level parameters using XML script associated with the one or more BSP-chipset level parameters.
This invention relates to real-time adjustment of board support package (BSP) and chipset parameters in computing systems. The problem addressed is the need for dynamic optimization of hardware performance and power efficiency by modifying low-level system parameters without manual intervention or system reboots. The apparatus includes a processor configured to adjust BSP-chipset level parameters in real time based on pre-loaded system conditions. These parameters control hardware behavior, such as power states, clock speeds, and memory configurations. The processor communicates with the chipset to modify these parameters using XML scripts specifically associated with each parameter. The XML scripts define the adjustments required for different operating conditions, allowing the system to adapt to workload changes, thermal conditions, or power constraints automatically. This approach enables efficient hardware management without requiring firmware updates or hardware redesigns, improving system responsiveness and energy efficiency. The invention is particularly useful in embedded systems, servers, and high-performance computing environments where real-time parameter tuning is critical for optimal performance.
3. The apparatus of claim 1 , wherein the one or more BSP-chipset level parameters comprise at least one of the following: screen brightness, LED blinking behavior, LED color, speaker volume, microphone gain, noise cancellation, echo cancellation, battery performance, keypad mapping, touch screen calibration, a WiFi profile, WWAN carrier selection, or scanner beep volume.
This invention relates to a system for dynamically adjusting hardware and software parameters at the Basic Input/Output System (BIOS) or chipset level of a computing device. The technology addresses the challenge of optimizing device performance, user experience, and power efficiency by enabling real-time modifications to low-level system parameters without requiring manual configuration or firmware updates. The apparatus includes a controller that monitors system conditions and user interactions to automatically adjust one or more BSP-chipset level parameters. These parameters include screen brightness, LED blinking behavior, LED color, speaker volume, microphone gain, noise cancellation, echo cancellation, battery performance, keypad mapping, touch screen calibration, WiFi profiles, WWAN carrier selection, and scanner beep volume. By dynamically configuring these settings, the system enhances functionality, reduces power consumption, and improves usability based on environmental factors, application demands, or user preferences. The invention ensures seamless integration with existing hardware and software components, allowing for adaptive adjustments without disrupting system stability. This approach eliminates the need for manual tuning, simplifying device management while maintaining optimal performance across various operating conditions. The solution is particularly useful in embedded systems, mobile devices, and IoT applications where efficient resource utilization and automated configuration are critical.
4. The apparatus of claim 1 , wherein the microphone is further configured to receive the one or more audio recording samples by collecting the one or more audio recording samples at pre-defined intervals over a pre-defined period of time.
This invention relates to audio recording systems, specifically an apparatus for capturing and processing audio samples. The apparatus includes a microphone configured to receive audio recording samples by collecting them at pre-defined intervals over a pre-defined period of time. This interval-based sampling approach allows for controlled and structured audio data acquisition, which can be useful in applications requiring periodic monitoring or analysis of sound environments. The apparatus may also include a processor to analyze the collected audio samples, enabling tasks such as noise detection, voice recognition, or environmental monitoring. The pre-defined intervals and period ensure consistent data collection, reducing variability and improving reliability in audio analysis. This method of structured sampling can be applied in various fields, including security systems, smart home devices, industrial monitoring, and healthcare, where periodic audio data is essential for decision-making or automation. The invention addresses the need for efficient and systematic audio data collection, overcoming challenges related to continuous recording, such as storage limitations and processing overhead. By capturing audio at specified intervals, the system optimizes resource usage while maintaining the necessary data granularity for accurate analysis.
5. The apparatus of claim 1 , wherein the processor is further in communication with one or more sensors and configured to receive one or more sensed conditions from the one or more sensors by communicating with the one or more sensors.
A system for monitoring and processing environmental or operational conditions includes a processor in communication with one or more sensors. The processor receives sensed conditions, such as temperature, pressure, or motion, from the sensors via direct or indirect communication channels. The sensors may be embedded in a device, attached externally, or part of a separate monitoring system. The processor analyzes the received data to detect anomalies, trigger alerts, or adjust system operations based on predefined thresholds or machine learning models. This enables real-time monitoring and automated responses in applications like industrial machinery, smart environments, or healthcare devices. The system may also include data storage for logging sensed conditions over time, allowing for historical analysis and predictive maintenance. The communication between the processor and sensors may use wired or wireless protocols, ensuring reliable data transmission even in dynamic environments. The apparatus ensures accurate and timely condition monitoring, improving system efficiency and safety.
6. The apparatus of claim 5 , wherein the processor is further configured to associate the sensed conditions with the pre-loaded condition when determining the pre-loaded condition.
This invention relates to an apparatus for monitoring and analyzing environmental or operational conditions, particularly in industrial, automotive, or IoT applications. The problem addressed is the need to accurately detect and classify real-time conditions by comparing them to pre-loaded reference conditions, ensuring reliable decision-making or system adjustments. The apparatus includes a sensor system to detect environmental or operational parameters such as temperature, pressure, or vibration. A processor analyzes the sensed data and compares it to pre-loaded condition profiles stored in memory. The processor is configured to associate the sensed conditions with the pre-loaded condition when determining the pre-loaded condition, meaning it correlates incoming sensor data with stored reference data to identify matches or deviations. This association helps in accurately classifying the current state of the system or environment. The apparatus may also include a communication module to transmit the analyzed data to external systems for further processing or control actions. The pre-loaded conditions can be updated or modified based on new data or user inputs, ensuring adaptability. The system may further include a user interface for displaying the sensed conditions, their associations with pre-loaded conditions, and any alerts or recommendations derived from the analysis. This technology is useful in predictive maintenance, safety monitoring, or automated control systems where real-time condition assessment is critical. The apparatus ensures that sensed conditions are reliably matched to known reference states, improving decision accuracy and system performance.
7. The apparatus of claim 5 , wherein the one or more sensors comprise at least one of the following: an accelerometer, a gyroscope, a scanner, global positioning system, WiFi, Wan, a proximity sensor, an ambient light sensor, a digital compass, or a microphone.
This invention relates to an apparatus equipped with multiple sensors for environmental monitoring and data collection. The apparatus is designed to gather and process data from various sources to enhance situational awareness, navigation, or user interaction. The sensors include an accelerometer for detecting motion and orientation, a gyroscope for measuring angular velocity, a scanner for capturing visual or barcode data, a global positioning system (GPS) for location tracking, WiFi and WAN (Wide Area Network) for connectivity and signal strength analysis, a proximity sensor for detecting nearby objects, an ambient light sensor for measuring light conditions, a digital compass for directional heading, and a microphone for audio input. These sensors enable the apparatus to perform tasks such as motion tracking, environmental mapping, location-based services, and user input detection. The combination of these sensors allows for comprehensive data collection, improving accuracy and functionality in applications like navigation systems, security devices, or smart environments. The apparatus may integrate the sensor data to provide real-time feedback or trigger specific actions based on detected conditions.
8. The apparatus of claim 1 , wherein the processor is further configured to analyze the one or more audio recording samples to determine the background noise intensity by applying a fast fourier transformation (FFT) algorithm or a similar algorithm, the FFT algorithm or the similar algorithm resulting in a decibel value representing the background noise intensity.
This invention relates to audio processing systems designed to analyze background noise in recorded audio samples. The problem addressed is the need for accurate and efficient measurement of background noise levels in audio recordings, which is critical for applications such as speech recognition, noise cancellation, and audio quality assessment. The apparatus includes a processor configured to analyze one or more audio recording samples to determine background noise intensity. The processor applies a Fast Fourier Transform (FFT) algorithm or a similar algorithm to the audio samples. The FFT algorithm converts the time-domain audio signal into the frequency domain, allowing for the extraction of frequency components and their respective amplitudes. The resulting data is then used to compute a decibel value representing the background noise intensity. This decibel value provides a quantitative measure of the noise level, enabling further processing or decision-making based on the noise characteristics. The use of FFT or similar algorithms ensures that the noise analysis is both precise and computationally efficient. The decibel value output can be used in various applications, such as adjusting audio processing parameters, filtering out noise, or improving speech recognition accuracy. The system is particularly useful in environments where background noise varies significantly, requiring real-time or near-real-time noise level assessment.
9. The apparatus of claim 1 , wherein the processor is further configured to: receive additional audio recording samples of the environment in which the apparatus is located after causing the one or more BSP-chipset level parameters to be adjusted; analyze the additional audio recording samples to determine a second background noise intensity; determine a second pre-loaded condition by associating the second background noise intensity with the second pre-loaded condition selected from the set of pre-loaded conditions stored in the database; and cause the same or different one or more BSP-chipset level parameters to be adjusted in real time based on the second pre-loaded condition in response to receiving the additional audio recording samples.
This invention relates to an apparatus for dynamically adjusting audio processing parameters in response to environmental background noise. The apparatus includes a processor and a database storing pre-loaded conditions associated with different background noise intensities. The processor receives audio samples from the environment, analyzes them to determine a background noise intensity, and selects a pre-loaded condition from the database based on the intensity. The processor then adjusts one or more BSP-chipset level parameters—such as gain, filter settings, or noise suppression levels—to optimize audio performance according to the selected condition. The apparatus continuously monitors the environment, receiving additional audio samples, analyzing them to determine updated noise intensities, and adjusting the parameters in real time based on the latest pre-loaded condition. This allows the system to adapt dynamically to changing noise levels, improving audio clarity and performance in varying environments. The adjustments may involve the same or different parameters depending on the new noise conditions. The invention ensures real-time optimization of audio processing by leveraging pre-defined conditions tailored to specific noise scenarios.
10. The apparatus of claim 9 , wherein the processor is further configured to receive the additional audio recording samples after a pre-defined period of time has passed since the processor caused the one or more BSP-chipset level parameters to be adjusted in real time based on the pre-loaded condition by monitoring a time delay after the one or more BSP-chipset level parameters.
This invention relates to real-time audio processing in computing devices, specifically adjusting hardware-level parameters to optimize audio performance based on pre-loaded conditions. The problem addressed is the need for dynamic adjustment of audio processing parameters at the Basic Input/Output System (BIOS) or chipset level to improve audio quality, reduce latency, or enhance power efficiency in response to changing conditions. The apparatus includes a processor configured to monitor and adjust one or more BIOS or chipset-level parameters in real time based on pre-loaded conditions. These conditions may include environmental factors, device usage patterns, or specific audio processing requirements. The processor can dynamically modify parameters such as sample rates, buffer sizes, or power states to optimize performance. Additionally, the processor is configured to receive additional audio recording samples after a pre-defined time delay following the adjustment of these parameters. This delay allows the system to assess the impact of the adjustments before further processing. The apparatus may also include a memory for storing the pre-loaded conditions and a communication interface for transmitting or receiving audio data. The system ensures that audio processing remains adaptive and responsive to real-time conditions, improving overall audio performance in computing devices.
11. The apparatus of claim 1 , wherein the one or more BSP-chipset level parameters comprise a noise cancellation parameter and the noise cancellation parameter is caused to be adjusted in real time when the background noise intensity is determined to be outside a threshold level associated with the pre-loaded condition.
This invention relates to noise cancellation in computing systems, specifically adjusting noise cancellation parameters at the Basic Input/Output System (BIOS) or chipset level to improve audio performance. The problem addressed is the inability of existing systems to dynamically adapt noise cancellation settings in real time based on changing background noise conditions, leading to suboptimal audio quality. The apparatus includes a computing system with a processor, memory, and a noise cancellation module. The system monitors background noise intensity and compares it to predefined threshold levels associated with pre-loaded conditions (e.g., quiet, moderate, or loud environments). When the background noise exceeds or falls below these thresholds, the system adjusts noise cancellation parameters in real time to optimize audio output. These parameters may include filter settings, gain adjustments, or other noise suppression algorithms. The system also includes a parameter adjustment module that modifies the noise cancellation settings dynamically, ensuring continuous adaptation to varying noise levels. This real-time adjustment prevents audio distortion or excessive suppression, enhancing user experience in different environments. The invention improves upon prior art by integrating noise cancellation control at the BIOS or chipset level, allowing deeper system-level adjustments that are more responsive than application-level solutions.
12. The apparatus of claim 7 , wherein the one or more BSP-chipset level parameters comprise a LED blinking behavior parameter and the LED blinking behavior parameter is caused to be adjusted in real time when the one or more sensed conditions indicate the apparatus is in motion.
This invention relates to a computing apparatus with a baseboard management controller (BMC) that adjusts LED blinking behavior based on real-time motion detection. The apparatus includes a BMC, a chipset, and one or more sensors that detect conditions such as motion. The BMC monitors these conditions and dynamically adjusts LED blinking behavior in response. For example, if the sensors indicate the apparatus is in motion, the BMC modifies the LED blinking pattern to signal an active or alert state. The adjustment occurs at the BSP-chipset level, meaning the changes are implemented through low-level firmware or hardware interactions between the BMC and the chipset. This allows for immediate and precise control over LED behavior without requiring higher-level software intervention. The system ensures that LED indicators accurately reflect the device's operational state, improving user awareness and system monitoring. The invention is particularly useful in environments where physical movement of the apparatus should trigger visual feedback, such as in portable or mobile computing devices.
13. The apparatus of claim 1 , wherein the processor is further configured to calibrate the microphone to collect background noise by collecting the audio recording samples in an environment with a low background noise intensity.
This invention relates to audio processing systems, specifically improving microphone calibration for accurate background noise measurement. The problem addressed is the difficulty in obtaining reliable background noise data when microphones are calibrated in environments with varying or high noise levels, leading to inaccurate noise profiles that degrade audio processing performance. The apparatus includes a processor and a microphone, where the processor is configured to calibrate the microphone by collecting audio recording samples in an environment with low background noise intensity. This ensures that the collected samples accurately represent the true background noise characteristics, minimizing interference from external sounds. The calibration process involves analyzing the audio samples to establish a baseline noise profile, which can then be used to enhance noise suppression, speech recognition, or other audio processing tasks. The system may also include additional components, such as a memory for storing calibration data or an interface for adjusting microphone settings based on the collected samples. By calibrating the microphone in a quiet environment, the apparatus ensures that subsequent noise reduction or audio analysis operations are more precise and effective. This approach is particularly useful in applications like voice assistants, hearing aids, or audio recording devices where accurate noise profiling is critical.
14. A method of adjusting board support package (BSP)-chipset level parameters in response to changes in an environment in which a microphone is located, the method comprising: receiving one or more audio recording samples from the microphone of the environment in which the microphone is located; analyzing the one or more audio recording samples to determine a background noise intensity; determining a customization profile by associating the background noise intensity with a pre-loaded condition selected from a set of pre-loaded conditions stored in a database, wherein the pre-loaded condition comprises one or more values that define the customization profile including a predefined chipset configuration profile having a chipset specification defined in a XML file; and causing one or more BSP-chipset level parameters to be adjusted in real time by applying the chipset specification of the customization profile, wherein the one or more BSP-chipset level parameters include one or more operational parameters associated with at least one hardware unit or a chipset in a user device and accessible through a BSP, wherein causing the one or more BSP-chipset level parameters to be adjusted in real time by applying the chipset specification of the customization profile comprises adjusting operational parameters within a broader range than accessible on a user interface or adjusting operational parameters not accessible on the user interface.
This invention relates to dynamically adjusting board support package (BSP)-chipset level parameters in response to environmental changes affecting a microphone. The problem addressed is the need to optimize audio performance in varying noise conditions by fine-tuning low-level hardware parameters that are typically inaccessible or limited through standard user interfaces. The method involves capturing audio samples from a microphone in the environment and analyzing them to determine background noise intensity. Based on this analysis, a customization profile is selected from a database of pre-loaded conditions, each associated with specific noise levels. The selected profile includes a predefined chipset configuration defined in an XML file, which specifies adjustments to BSP-chipset level parameters. These parameters control hardware units or chipset operations in a user device and are accessible through the BSP. The method then applies the chipset specification from the customization profile to adjust the BSP-chipset parameters in real time. Unlike standard user interfaces, which may restrict parameter adjustments to a narrow range or exclude certain settings, this approach allows for broader or otherwise inaccessible parameter modifications. This ensures optimal audio performance by dynamically adapting to environmental noise conditions.
15. The method of claim 14 , wherein causing the one or more BSP-chipset level parameters to be adjusted in real time based on the pre-loaded condition comprises communicating with the chipset to modify the one or more BSP-chipset level parameters.
This invention relates to real-time adjustment of chipset parameters in computing systems to optimize performance under specific conditions. The problem addressed is the static configuration of chipset parameters, which can lead to suboptimal performance or inefficiency in varying operational conditions. The solution involves dynamically modifying chipset-level parameters in real time based on pre-loaded conditions, such as workload type, thermal thresholds, or power constraints. The method includes monitoring system conditions and adjusting one or more chipset parameters, such as voltage, frequency, or power states, to improve performance, reduce power consumption, or enhance thermal management. The adjustments are made by communicating directly with the chipset to modify these parameters dynamically. This real-time adaptation ensures the system operates efficiently under different conditions without manual intervention. The invention may also involve pre-loading specific conditions or profiles that define the optimal chipset parameter settings for various scenarios. These profiles can be based on historical data, predictive analytics, or predefined rules. The system continuously evaluates current conditions against these profiles and applies the necessary adjustments to maintain optimal performance. By enabling real-time parameter adjustments at the chipset level, the invention improves system responsiveness, energy efficiency, and thermal management, particularly in high-performance computing environments. This approach is applicable to various computing devices, including servers, workstations, and embedded systems.
16. The method of claim 14 , wherein the one or more BSP-chipset level parameters comprise at least one of the following: screen brightness, LED blinking behavior, LED color, speaker volume, microphone gain, noise cancellation, echo cancellation, battery performance, keypad mapping, touch screen calibration, a WiFi profile, WWAN carrier selection, or scanner beep volume.
This invention relates to a method for configuring hardware parameters at the Basic Input/Output System (BIOS) or chipset level of a computing device. The method addresses the challenge of efficiently managing and adjusting low-level hardware settings that affect device performance, user experience, and functionality. These parameters are typically difficult to modify after manufacturing due to their deep integration into the system firmware. The method involves dynamically configuring one or more hardware parameters at the BIOS or chipset level, allowing for adjustments to settings such as screen brightness, LED blinking behavior, LED color, speaker volume, microphone gain, noise cancellation, echo cancellation, battery performance, keypad mapping, touch screen calibration, WiFi profiles, WWAN carrier selection, and scanner beep volume. These parameters are critical for optimizing device operation, enhancing user interaction, and ensuring compatibility with different environments or use cases. By enabling these adjustments at the firmware level, the method provides greater flexibility and control over hardware behavior without requiring physical modifications or extensive software updates. This approach is particularly useful for devices that need to adapt to varying conditions or user preferences while maintaining consistent performance and reliability.
17. The method of claim 14 , wherein receiving the one or more audio recording samples from the microphone comprises receiving the one or more audio recording samples at pre-defined intervals over a pre-defined period of time.
This invention relates to audio recording systems, specifically methods for capturing and processing audio samples from a microphone. The problem addressed is the need for efficient and controlled audio data collection, particularly in applications requiring periodic sampling over a defined duration. The method involves receiving audio recording samples from a microphone at pre-defined intervals over a pre-defined period of time. This ensures consistent and structured data collection, which can be useful for monitoring, analysis, or real-time processing. The intervals and duration can be adjusted based on the application, such as environmental monitoring, voice recognition, or acoustic event detection. The broader system includes a microphone for capturing audio and a processing unit that manages the sampling process. The processing unit may also filter, compress, or transmit the collected samples for further analysis. The method ensures that audio data is collected in a systematic manner, reducing gaps or overlaps in recordings. This approach is particularly valuable in scenarios where continuous monitoring is impractical or where power efficiency is a concern, as it allows for controlled sampling rather than constant recording. The pre-defined intervals and duration can be configured to optimize performance based on the specific requirements of the application.
18. The method of claim 14 , further comprising receiving one or more sensed conditions from one or more sensors by communicating with the one or more sensors.
A system and method for monitoring and managing environmental or operational conditions using sensor data. The invention addresses the need for real-time condition monitoring to improve decision-making, safety, or efficiency in various applications such as industrial processes, smart buildings, or environmental monitoring. The system includes one or more sensors that detect and measure physical conditions like temperature, pressure, humidity, or motion. These sensors transmit the sensed data to a central processing unit or controller, which receives and processes the information. The system may also include communication interfaces to facilitate data exchange between the sensors and the controller. The controller analyzes the received sensor data to detect anomalies, trigger alerts, or adjust system parameters automatically. The invention may further integrate with external systems or databases to enhance data analysis or reporting. The method ensures continuous monitoring and adaptive responses to changing conditions, improving operational reliability and performance. The system can be deployed in diverse environments, including manufacturing plants, smart homes, or environmental monitoring stations, to optimize resource usage and enhance safety.
19. The method of claim 18 , further comprising associating the one or more sensed conditions with the pre-loaded condition when determining the pre-loaded condition.
A system and method for monitoring and analyzing environmental or operational conditions involves sensing one or more conditions using one or more sensors, where the sensed conditions may include temperature, pressure, humidity, motion, or other relevant parameters. The system compares the sensed conditions to a pre-loaded condition, which is a predefined set of conditions stored in a database or memory. The comparison determines whether the sensed conditions match or deviate from the pre-loaded condition, enabling real-time monitoring and decision-making. The method further includes associating the sensed conditions with the pre-loaded condition during the comparison process to improve accuracy and relevance. This association may involve mapping sensor data to specific parameters of the pre-loaded condition, ensuring that the comparison is contextually appropriate. The system may generate alerts, trigger actions, or log data based on the comparison results, facilitating automated responses or manual interventions. The method is applicable in industrial, medical, automotive, or environmental monitoring applications where precise condition tracking is essential. The pre-loaded condition may be dynamically updated or adjusted based on new data or user inputs, allowing the system to adapt to changing requirements. The method ensures reliable and efficient condition monitoring by leveraging sensor data and predefined reference conditions.
20. The method of claim 18 , wherein the one or more sensors comprise at least one of the following: an accelerometer, a scanner, global positioning system, WiFi, Wan, a proximity sensor, or a light sensor.
This invention relates to a system for monitoring and analyzing the movement and location of objects, particularly in industrial or logistics environments, to improve tracking, security, and operational efficiency. The system addresses challenges in accurately detecting and recording the position, orientation, and environmental conditions of objects in real-time, which is critical for applications such as inventory management, asset tracking, and automated logistics. The system includes one or more sensors attached to or integrated with the objects being monitored. These sensors may include an accelerometer to measure movement and vibrations, a scanner for identifying objects via barcodes or RFID tags, a global positioning system (GPS) for outdoor location tracking, WiFi or WAN (Wide Area Network) for indoor positioning and connectivity, a proximity sensor to detect nearby objects or obstacles, and a light sensor to monitor environmental conditions. The sensors collect data continuously or at predefined intervals and transmit it to a central processing unit for analysis. The central processing unit processes the sensor data to determine the object's location, movement patterns, and environmental context. This information is then used to generate alerts, optimize routing, or trigger automated actions, such as adjusting conveyor belts or notifying personnel of potential issues. The system enhances operational visibility, reduces errors, and improves decision-making in dynamic environments.
21. The method of claim 14 , wherein analyzing the one or more audio recording samples to determine the background noise intensity comprises applying a fast fourier transformation (FFT) algorithm or a similar algorithm, the FFT algorithm or the similar algorithm resulting in a decibel value representing the background noise intensity.
This invention relates to audio processing techniques for analyzing background noise in audio recordings. The problem addressed is the need to accurately measure background noise intensity in audio samples to improve audio quality, noise reduction, or signal processing applications. The method involves analyzing one or more audio recording samples to determine background noise intensity. This is achieved by applying a Fast Fourier Transform (FFT) algorithm or a similar algorithm to the audio data. The FFT algorithm converts the time-domain audio signal into the frequency domain, allowing for the extraction of frequency components. The resulting output of the FFT or similar algorithm is a decibel value, which quantitatively represents the background noise intensity in the audio sample. This decibel value can then be used for further processing, such as noise filtering, audio enhancement, or quality assessment. The FFT or similar algorithm effectively decomposes the audio signal into its constituent frequencies, enabling precise measurement of noise levels across different frequency bands. This approach ensures accurate and reliable noise intensity determination, which is critical for applications requiring high-fidelity audio analysis or noise suppression. The method can be applied in various fields, including telecommunications, audio editing, speech recognition, and environmental noise monitoring.
22. The method of claim 14 , further comprising: receiving additional audio recording samples after causing the one or more BSP-chipset level parameters to be adjusted; analyzing the additional audio recording samples to determine a second background noise intensity; determining a second pre-loaded condition by associating the second background noise intensity with the second pre-loaded condition selected from the set of pre-loaded conditions stored in the database; and causing the same or different one or more BSP-chipset level parameters to be adjusted in real time based on the second pre-loaded condition in response to receiving the additional audio recording samples.
This invention relates to adaptive audio processing in electronic devices, specifically for dynamically adjusting background noise suppression based on real-time environmental conditions. The problem addressed is the static nature of conventional noise suppression settings, which fail to adapt to changing acoustic environments, leading to suboptimal audio quality. The method involves continuously monitoring audio recordings from a device's microphone to assess background noise intensity. A database stores pre-loaded conditions, each linked to specific noise intensity ranges and corresponding optimal audio processing parameters. When a new audio sample is received, its noise intensity is analyzed and matched to the most relevant pre-loaded condition. Based on this match, the device adjusts one or more low-level hardware parameters, such as those controlled by the Board Support Package (BSP) or chipset, to optimize noise suppression in real time. The method further includes iterative adjustments. After initial parameter changes, additional audio samples are collected and analyzed to determine a new noise intensity. This updated intensity is again associated with a pre-loaded condition, which may trigger further adjustments to the same or different hardware parameters. This closed-loop process ensures continuous adaptation to evolving acoustic environments, improving audio clarity and user experience. The system dynamically balances noise suppression and audio fidelity without manual intervention.
23. The method of claim 22 , wherein receiving the additional audio recording samples occurs after a pre-defined period of time has passed since causing the one or more BSP-chipset level parameters to be adjusted in real time based on the pre-loaded condition.
This invention relates to real-time audio processing in computing devices, specifically adjusting hardware-level parameters to optimize audio performance under specific conditions. The method involves monitoring audio recordings to detect deviations from expected performance, then dynamically adjusting parameters at the Basic System Parameters (BSP) chipset level to correct these deviations. The system pre-loads condition-specific parameter adjustments, allowing rapid real-time modifications when triggered by detected audio anomalies. The method further includes receiving additional audio samples after a predefined delay following the initial parameter adjustments, enabling continuous refinement of the audio processing. This approach ensures consistent audio quality by dynamically adapting hardware settings in response to real-time performance data, addressing issues like distortion, latency, or signal degradation that arise during audio capture or playback. The system may apply these adjustments across various audio conditions, such as different environments, device states, or user preferences, improving overall audio fidelity without manual intervention. The delayed sample collection allows the system to verify the effectiveness of the adjustments before further refinements, ensuring stability and accuracy in the audio processing pipeline.
24. The method of claim 14 , wherein the one or more BSP-chipset level parameters comprise a noise cancellation parameter and the noise cancellation parameter is adjusted in real time when the background noise intensity is determined to be outside a threshold level associated with the pre-loaded condition.
This invention relates to real-time adjustment of noise cancellation parameters in computing systems to optimize audio performance based on background noise conditions. The method involves monitoring background noise intensity and dynamically adjusting noise cancellation settings at the Basic Input/Output System (BIOS) or chipset level when detected noise levels exceed predefined thresholds. The system includes a noise detection module that continuously evaluates ambient noise and compares it against stored threshold values associated with specific operating conditions. When noise levels fall outside acceptable ranges, the method automatically modifies noise cancellation parameters to maintain audio clarity. This adjustment process occurs in real time, ensuring immediate response to changing environmental conditions. The invention also incorporates a parameter adjustment module that implements the necessary changes to noise cancellation settings, which may include filtering algorithms, gain adjustments, or other audio processing techniques. The system may further include a feedback loop to verify the effectiveness of the adjustments and refine parameters as needed. This approach improves audio quality in varying noise environments without requiring manual intervention, particularly beneficial for applications where consistent audio performance is critical, such as voice communications or multimedia playback.
25. The method of claim 18 , wherein the one or more BSP-chipset level parameters comprise a LED blinking behavior parameter and the LED blinking behavior parameter is adjusted in real time when the one or more sensed conditions indicate the apparatus is in motion.
This invention relates to adjusting LED blinking behavior in electronic devices based on real-time motion detection. The technology addresses the problem of static LED indicators that do not adapt to dynamic usage scenarios, such as when a device is in motion, which can lead to inefficient power consumption or unintended user notifications. The method involves monitoring one or more sensed conditions, such as motion, to determine whether the device is in motion. When motion is detected, a LED blinking behavior parameter is dynamically adjusted in real time. This parameter controls aspects like blinking frequency, duration, or pattern of the LED. The adjustment ensures the LED behavior aligns with the device's current state, improving user experience and power efficiency. The system may also include additional parameters at the BSP-chipset level, such as power management settings or sensor calibration, which are similarly adjusted based on sensed conditions. The real-time adjustments are performed by a processing unit that interprets sensor data and modifies the LED behavior accordingly. This adaptive approach ensures the LED provides relevant feedback without unnecessary power drain or distractions.
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February 25, 2020
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